As is known, the processing of images acquired via SAR (Synthetic Aperture Radar) systems enables detecting the presence of moving objects in the observed scene. In the case of aerial or naval targets, the SAR images can also be effectively used for classifying the identified targets.
The movement of mobile objects on the ground (also known as ground movers), such as motor vehicles for example, has characteristics such that the currently available SAR systems do not provide satisfactory results.
One of the main causes of the scarce effectiveness of known SAR systems in acquiring images of objects moving on the ground derives from the fact that land transport vehicles are subject to vibration and rapid changes in direction. Critical vibrations may depend, for example, on uneven ground, while changes in direction may be due to simple corrections in trajectory by the driver while the vehicle is travelling along a stretch of road, even if substantially straight. Irregularities of this type generally entail vehicle displacements in the order of a few centimeters, i.e. quantities comparable with the central wavelength of the electromagnetic pulses emitted by the most common SAR systems. As SAR images are basically constructed from information on the phase of the reflected pulses received, it is evident that changes comparable with the wavelength of the signal, and totally unpredictable, generate errors that cannot be reduced within acceptable limits with conventional focusing methods, which assume either rectilinear motion or knowing the motion of the target beforehand. In fact, these methods use tracking algorithms to obtain the overall speed of the detected object to compensate for the effects of motion in the SAR images. However, at present, tracking algorithms that are so sophisticated as to follow the motion of objects on the ground with sufficient precision to obtain satisfactorily focused images are unavailable (the highest accuracy levels are in the order of meters per second, when instead a precision of millimeters per second would be needed).
Another aspect that makes it difficult to produce SAR images of objects moving on the ground is the choice of the moment when to start processing. In fact, it is not enough to detect the presence of a moving object, but it is also necessary that the object has an adequate angular velocity with respect to the SAR observer. A known solution, albeit unsatisfactory, makes use of roadmaps related to the observed scene, in practice assuming that the moving object is a means of transport travelling along a road. Once the presence of an object moving on the ground has been detected, a tracking algorithm calculates the motion. On the basis of the position in the SAR images and the trajectory characteristics, the moving object is placed on a road on the map and processing commences when it is possible to determine that the moving object is approaching a curved stretch that offers the necessary and assured angular rotation usable for generating the SAR image. The effectiveness is therefore modest and, in addition, it is necessary to have maps and carry out operations to correlate the position of the moving object in the SAR images to points on the maps.